renamed train_batch_size into batch_size

Author: vfdev-5

src/templates/template-common/config.yaml

@@ -1,6 +1,6 @@
 seed: 777
 data_path: ./
-train_batch_size: 32
+batch_size: 32
 eval_batch_size: 32
 num_workers: 4
 max_epochs: 20

src/templates/template-text-classification/data.py

@@ -61,7 +61,7 @@ def setup_data(config):
 
     dataloader_train = idist.auto_dataloader(
         dataset_train,
-        batch_size=config.train_batch_size,
+        batch_size=config.batch_size,
         num_workers=config.num_workers,
         shuffle=True,
         drop_last=True,

src/templates/template-text-classification/test_all.py

@@ -27,7 +27,7 @@ def test_setup_data():
         model="bert-base-uncased",
         tokenizer_dir="/tmp/tokenizer",
         max_length=1,
-        train_batch_size=1,
+        batch_size=1,
         eval_batch_size=1,
         num_workers=1,
     )

src/templates/template-vision-classification/data.py

@@ -10,7 +10,7 @@ def setup_data(config: Any):
 
     Parameters
     ----------
-    config: needs to contain `data_path`, `train_batch_size`, `eval_batch_size`, and `num_workers`
+    config: needs to contain `data_path`, `batch_size`, `eval_batch_size`, and `num_workers`
     """
     #::: if (it.use_dist) { :::#
     local_rank = idist.get_local_rank()
@@ -59,7 +59,7 @@ def setup_data(config: Any):
 
     dataloader_train = idist.auto_dataloader(
         dataset_train,
-        batch_size=config.train_batch_size,
+        batch_size=config.batch_size,
         shuffle=True,
         num_workers=config.num_workers,
     )

src/templates/template-vision-classification/test_all.py

@@ -25,7 +25,7 @@ def set_up():
 
 @pytest.mark.skipif(os.getenv("RUN_SLOW_TESTS", 0) == 0, reason="Skip slow tests")
 def test_setup_data():
-    config = Namespace(data_path="~/data", train_batch_size=1, eval_batch_size=1, num_workers=0)
+    config = Namespace(data_path="~/data", batch_size=1, eval_batch_size=1, num_workers=0)
     dataloader_train, dataloader_eval = setup_data(config)
 
     assert isinstance(dataloader_train, DataLoader)

src/templates/template-vision-dcgan/data.py

@@ -10,7 +10,7 @@ def setup_data(config: Any):
 
     Parameters
     ----------
-    config: needs to contain `data_path`, `train_batch_size`, `eval_batch_size`, and `num_workers`
+    config: needs to contain `data_path`, `batch_size`, `eval_batch_size`, and `num_workers`
     """
     #::: if (it.use_dist) { :::#
     local_rank = idist.get_local_rank()
@@ -49,7 +49,7 @@ def setup_data(config: Any):
 
     dataloader_train = idist.auto_dataloader(
         dataset_train,
-        batch_size=config.train_batch_size,
+        batch_size=config.batch_size,
         shuffle=True,
         num_workers=config.num_workers,
     )

src/templates/template-vision-dcgan/main.py

@@ -39,7 +39,7 @@ def run(local_rank: int, config: Any):
     device = idist.device()
 
     fixed_noise = torch.randn(
-        config.train_batch_size // idist.get_world_size(),
+        config.batch_size // idist.get_world_size(),
         config.z_dim,
         1,
         1,

src/templates/template-vision-dcgan/test_all.py

@@ -26,7 +26,7 @@ def set_up():
 
 @pytest.mark.skipif(os.getenv("RUN_SLOW_TESTS", 0) == 0, reason="Skip slow tests")
 def test_setup_data():
-    config = Namespace(data_path="~/data", train_batch_size=1, eval_batch_size=1, num_workers=0)
+    config = Namespace(data_path="~/data", batch_size=1, eval_batch_size=1, num_workers=0)
     dataloader_train, dataloader_eval, _ = setup_data(config)
 
     assert isinstance(dataloader_train, DataLoader)
@@ -60,7 +60,7 @@ def test_models():
 
 def test_setup_trainer():
     model, optimizer, device, loss_fn, batch = set_up()
-    config = Namespace(use_amp=False, train_batch_size=2, z_dim=100)
+    config = Namespace(use_amp=False, batch_size=2, z_dim=100)
     trainer = setup_trainer(config, model, model, optimizer, optimizer, loss_fn, device, None)
     trainer.run([batch, batch])
     assert isinstance(trainer.state.output, dict)

src/templates/template-vision-dcgan/trainers.py

@@ -21,9 +21,9 @@ def setup_trainer(
 ) -> Union[Engine, DeterministicEngine]:
     ws = idist.get_world_size()
 
-    real_labels = torch.ones(config.train_batch_size // ws, device=device)
-    fake_labels = torch.zeros(config.train_batch_size // ws, device=device)
-    noise = torch.randn(config.train_batch_size // ws, config.z_dim, 1, 1, device=device)
+    real_labels = torch.ones(config.batch_size // ws, device=device)
+    fake_labels = torch.zeros(config.batch_size // ws, device=device)
+    noise = torch.randn(config.batch_size // ws, config.z_dim, 1, 1, device=device)
 
     def train_function(engine: Union[Engine, DeterministicEngine], batch: Any):
         model_g.train()

src/templates/template-vision-segmentation/data.py

@@ -124,7 +124,7 @@ def setup_data(config: Namespace):
     dataloader_train = idist.auto_dataloader(
         dataset_train,
         shuffle=True,
-        batch_size=config.train_batch_size,
+        batch_size=config.batch_size,
         num_workers=config.num_workers,
         drop_last=True,
     )